def many_dists():
a = hp_choice('a', [0, 1, 2])
b = hp_randint('b', 10)
c = hp_uniform('c', 4, 7)
d = hp_loguniform('d', -2, 0)
e = hp_quniform('e', 0, 10, 3)
f = hp_qloguniform('f', 0, 3, 2)
g = hp_normal('g', 4, 7)
h = hp_lognormal('h', -2, 2)
i = hp_qnormal('i', 0, 10, 2)
j = hp_qlognormal('j', 0, 2, 1)
z = a + b + c + d + e + f + g + h + i + j
return {'loss': scope.float(scope.log(1e-12 + z**2))}
def many_dists():
a=hp_choice('a', [0, 1, 2])
b=hp_randint('b', 10)
c=hp_uniform('c', 4, 7)
d=hp_loguniform('d', -2, 0)
e=hp_quniform('e', 0, 10, 3)
f=hp_qloguniform('f', 0, 3, 2)
g=hp_normal('g', 4, 7)
h=hp_lognormal('h', -2, 2)
i=hp_qnormal('i', 0, 10, 2)
j=hp_qlognormal('j', 0, 2, 1)
z = a + b + c + d + e + f + g + h + i + j
return {'loss': scope.float(scope.log(1e-12 + z ** 2))}
def many_dists():
a = hp.choice("a", [0, 1, 2])
b = hp.randint("b", 10)
bb = hp.randint("bb", 12, 25)
c = hp.uniform("c", 4, 7)
d = hp.loguniform("d", -2, 0)
e = hp.quniform("e", 0, 10, 3)
f = hp.qloguniform("f", 0, 3, 2)
g = hp.normal("g", 4, 7)
h = hp.lognormal("h", -2, 2)
i = hp.qnormal("i", 0, 10, 2)
j = hp.qlognormal("j", 0, 2, 1)
k = hp.pchoice("k", [(0.1, 0), (0.9, 1)])
z = a + b + bb + c + d + e + f + g + h + i + j + k
return {"loss": scope.float(scope.log(1e-12 + z ** 2)), "status": base.STATUS_OK}
def many_dists():
a = hp.choice('a', [0, 1, 2])
b = hp.randint('b', 10)
c = hp.uniform('c', 4, 7)
d = hp.loguniform('d', -2, 0)
e = hp.quniform('e', 0, 10, 3)
f = hp.qloguniform('f', 0, 3, 2)
g = hp.normal('g', 4, 7)
h = hp.lognormal('h', -2, 2)
i = hp.qnormal('i', 0, 10, 2)
j = hp.qlognormal('j', 0, 2, 1)
k = hp.pchoice('k', [(.1, 0), (.9, 1)])
z = a + b + c + d + e + f + g + h + i + j + k
return {'loss': scope.float(scope.log(1e-12 + z ** 2)),
'status': base.STATUS_OK}
